Retrieving 10-Year Monthly Returns for Multiple Mutual Funds via LSEG Workspace API in Python

nsk
nsk Newcomer

Hi,

I'm using LSEG Workspace for Students and trying to retrieve monthly returns for a list of mutual funds over the past 10 years using the API in Python. However, I haven't been able to find a function or endpoint that provides this type of time-series return data.

I've checked the documentation, but couldn't identify a clear way to obtain monthly return series for mutual funds over a historical period.

Could you please advise on:

  1. Whether monthly return data for mutual funds is available through the API?
  2. Which function, endpoint, or data field I should use?
  3. If possible, could you provide an example of the correct API call or Python code?

Thanks in advance for your help!

Answers

  • Jirapongse
    Jirapongse ✭✭✭✭✭

    @nsk

    Thank you for reaching out to us.

    You can use the LSEG Data Library for Python to retrieve data.

    The get_data method can be used to retrieve data of the TR.xxx fields. You can use the Data Item Browser tool to search for the TR fields and parameters. For example:

    ld.get_data(
        universe = ['AAPL.O'],
        fields = ['TR.TotalReturn1Mo.Date','TR.TotalReturn1Mo'],
        parameters = {'SDate':'2020-01-01','EDate':'2025-06-06','Frq':'M'})
    

    The get_history method can be used to retrieve data of the real-time fields (non-TR fields). You can ignore the fields parameter to retrieve all available historical real-time fields. For example:

    response = ld.get_history(
        universe = ["AAPL.O"],
        interval = '1M',
        start = "2020-01-01",end = "2025-06-30")
    

    The examples are available on GitHub.

    This forum is dedicated to software developers using LSEG APIs. The moderators on this forum do not have deep expertise in every bit of content available through LSEG products, which is required to answer content questions such as this one.

    The best resource for content questions is the Helpdesk support team, which can be reached by submitting queries through LSEG Support. The support team will either have the required content expertise ready available or can reach out to relevant content experts to get the answer for you.